The present invention relates generally to optimizing operation of a resonant system for inductive power transfer between a transmitter and receiver system, or a “wireless power transfer system”, and more particularly to optimizing parameters of “state variables” that affect an “operating point” of the resonant system. The invention also relates to performing the optimization in a way that results in the system being simpler, more flexible, and more cost-effective than is the case in prior systems.
A resonant inductive power transfer system includes an inductor and a capacitor that resonate at a fundamental frequency. It may be desirable to regulate the amount of current flowing through the inductor or the amount of voltage across the capacitor in order to regulate the intensity of the magnetic field generated by the inductor and thereby regulate the amount of power to be delivered to a load. The inductor current and the power delivered to the load is a function of the operating point of the resonant circuit. An operating point of the resonant system is a particular normal operating value of a particular state variable. In this example, the sinusoidal or quasi-sinusoidal inductor current and the sinusoidal or quasi-sinusoidal voltage across the resonant capacitor are state variables of the resonant system, and the amplitude and the phase of the inductor current and the amplitude and phase of the voltage across the resonant capacitor are parameters of those state variables. The amplitude and/or phase of a particular state variable may need to be determined or “extracted” in order to determine and/or regulate the state variable.
In a resonant system, several parameters may be optimized based on the resonant system operating point. The system operating point is determined by measurements of the phase and amplitude of one or more “state variables. Sampling the phase and amplitude of a state variable may require very fast analog to digital converters (ADCs), which usually are costly and consume a large amount of power.
Optimizing or regulating the amount of power that is being delivered from a transmitter to a receiver requires measuring parameters of one or more state variables that determine the transmitter-receiver system operating point. To achieve such measurements, known sub-sampling techniques (sometimes referred to as IF sampling, bandpass sampling, quadrature sampling, or simply sub-sampling) are utilized wherein a relatively high-frequency resonant signal is sampled at a much lower frequency, and then digital techniques are utilized to compute the amplitude and phase of the high-frequency resonant signal.
A reason for performing the optimization of a wireless power transfer system is that the system needs to be able to be optimized on a real-time basis, i.e., “on-the-fly”, because the load on the transmitter changes frequently and sometimes drastically. For example, various remote receivers or other loads may frequently become connected and/or disconnected, and that causes the system operating point (or points) to vary considerably and therefore become non-optimal.
Prior Art FIG. 1A shows a sinusoidal waveform 1 which represents a high fundamental frequency (e.g., roughly 6 MHZ) of a state variable of a resonant system, such as the sinusoidal voltage across a resonant capacitor or the corresponding sinusoidal current through the resonant inductor. Sampling points P1 and P2 represent “low-frequency sample points” at which values of waveform 1 are sampled for the purpose of extracting the amplitude and/or phase of the state variable of interest. (Although FIG. 1A illustrates a sinusoidal waveform, it could be quasi-sinusoidal waveform in which a portion of each cycle is non-sinusoidal.)
Prior Art FIG. 1B shows a digital system/technique for computing the amplitude and/or phase of waveform 1 from the two sampled values P1 and P2 in FIG. 1A. Sample P1 is measured at a sample time k−1 and has the value VCS1_DSAMP(k−1). Sample P2 is measured at sample time k and has the value VCS1_DSAMP(k).
To generate or “extract” the amplitude information, the value VCS1_DSAMP(k-1) of Sample P1 is squared, as indicated in block 5 of FIG. 1B, to produce the result VCS1_DSAMP(k-1))2 on path 6, which is provided as an input to a digital summing function 7. Similarly, value VCS1_DSAMP(k) of Sample P2 is squared, as indicated in block 13 of FIG. 1B to produce the result VCS1_DSAMP(k))2 on path 14, which is provided as an input to digital summing function 7. Digital summing function 7 provides the value (VCS1_DSAMP(k-1))2+(VCS1_DSAMP(k))2 on path 8, which is provided as an input to digital square root function 9. The result of the digital square root function 9 provides a representation of the amplitude of the signal represented by waveform 1 in FIG. 1A.
To generate or “extract” the phase information, both the value VCS1_DSAMP(k-1) of Sample P1 and the value VCS1_DSAMP(k) of Sample P2 are provided as inputs to circuitry in block 15 which performs an invert and sort function so as to generate a value/signal VCS1_I on path 16, which is coupled to block 19, and also to generate a value/signal VCS1_Q on path 17, which also is connected to block 19. In block 19, the arctangent function is performed on VCS1_I and VCS1_Q to generate the phase value/signal
      tan          -      1        ⁡      (                  V                  CS          ⁢                                          ⁢          1          ⁢          _Q                            V                  CS          ⁢                                          ⁢          1          ⁢          _I                      )  on path 20.
Explained somewhat differently, the sampling provides values corresponding to the expressions A*sine(ωt+φ), A*cosine(ωt+φ), −A*sine(ωt+φ), and −A*cosine(ωt+φ) at successive discrete times k−1 and k, k+1, k+2 and k+3. The squaring function generates the quantity A2 cosine2(ωt+φ)+A2 sine(ωt+φ), which corresponds to A2. Those two values are summed, which provides a value that represents A2. Then the square root of that value is computed to determine a value that represents the amplitude A of the selected state variable.
More specifically, a sinusoidal waveform VCS1(t)=A(t)*sin(2πfo*t+θ(t)) is sampled at discrete times t=k*n/(4*fo), where n is an odd integer and an asterisk (*) represents multiplication. These samples are referred to as VCS1_DSAMP(k). Sampling at these specific times provides the following.
For k=0, 4, 8, . . . and n odd=1, 5, 9 . . . :VCS1_DSAMP(k)=A(k)*sin θ(k))VCS1_DSAMP(k+1)=A(k+1)*cos(θ(k+1))VCS1_DSAMP(k+2)=−A(k+2)*sin(θ(k+2))VCS1_DSAMP(k+3)=−A(k+3)*cos(θ(k+3))Alternately, for k=0, 4, 8, . . . and n odd=3, 7, 11 . . . :VCS1_DSAMP(k)=A(k)*sin(θ(k))VCS1_DSAMP(k+1)=−A(k+1)*cos(θ(k+1))VCS1_DSAMP(k+2)=−A(k+2)*sin(θ(k+2))VCS1_DSAMP(k+3)=A(k+3)*cos(θ(k+3))Samples can be processed to remove the inversion and sorted into quadrature and in-phase pairs, as follows:VCS1_Q(m)=A(m)*sin(θ(m))VCS1_I(m+1)=A(m+1)*cos(θ(m+1))If the change in amplitude and phase for successive pairs of samples is small, i.e. A(m+1)˜A(m) and θ(m+1)˜θ(m), then the amplitude and phase can be recovered by processing sample pairs. For example using the assumption A(m+1)˜A(m) and θ(m+1)˜θ(m), then:A(m+1)=sqrt(V2CS1_Q(m)+V2CS1_I(m+1))where sqrt is the square root function.θ(m+1)=arctan(VCS1_Q(m)/VCS1_I(m+1))where arctan is the arctangent function.
One Prior Art reference which describes this technique is “Bandpass Signal Sampling and Coherent Detection” by W. M. Waters and B. R. Jarrett, in IEEE Transactions on Aerospace and Electronic Systems, Volume AES-18, Issue 6, 1982. This reference discloses that conversion of signals from IF (intermediate frequency) analog form into digital complex samples carrying phase and amplitude information has been implemented in the form of two parallel IF baseband converters operated in quadrature each followed by A/D converters to provide digitized in-phase “I” and quadrature “Q” components based on samples taken from the relatively low-frequency IF signal rather than the relatively high-frequency fundamental signal. The section entitled “Calculation of I and Q from IF Samples” on page 731 is especially relevant. Another relevant Prior Art reference is the article “A VLSI Demodulator for Digital RF Network Applications: Theory and Results” by Gary J. Saulnier, IEEE Journal on selected areas in communications, Volume 8, Number 8, October 1990. See the section “Subharmonic Sampling” on page 1503.
FIG. 2 is a block diagram of a generalized prior art wireless power transfer system. Block 200 includes a wireless power transfer system with a coupled inductor structure. The inductors and capacitors shown are parameters of a circuit model which includes 2 coils or inductors LK1 and LK2 and matching capacitors C1s and C2s. A signal source 30 and load 340,350 are also shown.
For the frequency ω=2πf, the capacitance of capacitor C1s is equal in magnitude to the inductance of model 200 inductor LK1, the capacitance of capacitor CM is equal in magnitude to the inductance of inductor LM, and the capacitance of capacitor C2s is equal in magnitude to the inductance of inductor LK2. Thus, at the frequency ω=2πf, the imaginary part of the reactance of each capacitor cancels out the imaginary part of the reactance of its corresponding inductor, and the circuit of FIG. 2 is impedance-matched for the frequency ω=2πf. In the ideal case the system appears to the power supply as a purely resistive load, allowing for improved power transfer. Impedance matching may be done at the design stage for a known operating frequency, or during operation for changing system conditions. For example, at least one of capacitors CM, C1s, and C2s may be implemented as variable capacitors to allow for tuning of the impedance matching during operation for changing system conditions. Variable capacitors, or other variable components, also allow for adjusting the resonant frequency of an associated resonant circuit.
It is well-known that if the transmitter coil/inductor is operating at resonance with a resonant capacitor in a resonant system, and if another coil in a receiver is located sufficiently close to the transmitter, that other “receiver” coil (which is connected to a capacitor such that the coil/inductor and capacitor have the same (or similar) resonance frequency as the transmitter circuit) will resonate with the magnetic field being generated by the transmitter coil. The receiver coil absorbs some of the transmitted energy if a load is connected to it, and this changes the operating point of the system including the transmitter and receiver, and therefore also changes the amplitude and phase of the one or more state variables of the system.
Thus, there is an unmet need for an improved way to optimize parameters of “state variables” that affect an operating point of a resonant system.
There also is an unmet need for an improved way to optimize operation of a resonant system in an inductive wireless power transmitter-receiver system in a way that provides a simpler, more flexible, and more cost-effective inductive wireless power transmitter-receiver system than is available in the prior art.
There also is an unmet need for an improved way to optimize operation of a resonant wireless system for transferring power.